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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels
0 0 0 0 ... 0 0 0
1 0 0 0 ... 0 0 0
2 0 0 0 ... 0 0 0
3 0 0 0 ... 0 0 0
4 0 0 0 ... 0 0 0
[5 rows x 44 columns]
Random Forest Accuracy = 0.9836033950617284
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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels
0 0 0 0 ... 0 0 0
1 0 0 0 ... 0 0 0
2 0 0 0 ... 0 0 0
3 0 0 0 ... 0 0 0
4 0 0 0 ... 0 0 0
[5 rows x 44 columns]
Random Forest Accuracy = 0.865940940940941
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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels
0 0 0 0 ... 0 0 0
1 0 0 0 ... 0 0 0
2 0 0 0 ... 0 0 0
3 0 0 0 ... 0 0 0
4 0 0 0 ... 0 0 0
[5 rows x 44 columns]
Random Forest Accuracy = 0.9033794210877544
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<Figure size 432x288 with 0 Axes>
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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels
0 0 0 0 ... 0 0 0
1 0 0 0 ... 0 0 0
2 0 0 0 ... 0 0 0
3 0 0 0 ... 0 0 0
4 0 0 0 ... 0 0 0
[5 rows x 44 columns]
Random Forest Accuracy = 0.9038267434100767
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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels
0 0 0 0 ... 0 0 0
1 0 0 0 ... 0 0 0
2 0 0 0 ... 0 0 0
3 0 0 0 ... 0 0 0
4 0 0 0 ... 0 0 0
[5 rows x 44 columns]
Random Forest Accuracy = 0.9001803887220554
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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels
0 0 0 0 ... 0 0 0
1 0 0 0 ... 0 0 0
2 0 0 0 ... 0 0 0
3 0 0 0 ... 0 0 0
4 0 0 0 ... 0 0 0
[5 rows x 44 columns]
Random Forest Accuracy = 0.8811373873873873
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Original Image Gabor1 Gabor2 ... Median s3 Variance s3 Labels
0 0 0 0 ... 0 0 0
1 0 0 0 ... 0 0 0
2 0 0 0 ... 0 0 0
3 0 0 0 ... 0 0 0
4 0 0 0 ... 0 0 0
[5 rows x 44 columns]
Random Forest Accuracy = 0.895925091758425
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Traceback (most recent call last):
File C:\Dev\Python\biomedical_term\Lib\site-packages\spyder_kernels\py3compat.py:356 in compat_exec
exec(code, globals, locals)
File c:\dev\python\biomedical_term\homew.py:468
plot(segmented_selected_perm,f"{ml_algo[k+1]} selected 'Permutation' estimated result")
File c:\dev\python\biomedical_term\homew.py:39 in plot
plt.show()
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\pyplot.py:446 in show
return _get_backend_mod().show(*args, **kwargs)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib_inline\backend_inline.py:90 in show
display(
File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\display_functions.py:298 in display
format_dict, md_dict = format(obj, include=include, exclude=exclude)
File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\formatters.py:179 in format
data = formatter(obj)
File C:\Dev\Python\biomedical_term\Lib\site-packages\decorator.py:232 in fun
return caller(func, *(extras + args), **kw)
File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\formatters.py:223 in catch_format_error
r = method(self, *args, **kwargs)
File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\formatters.py:340 in __call__
return printer(obj)
File C:\Dev\Python\biomedical_term\Lib\site-packages\IPython\core\pylabtools.py:152 in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backend_bases.py:2366 in print_figure
result = print_method(
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backend_bases.py:2232 in <lambda>
print_method = functools.wraps(meth)(lambda *args, **kwargs: meth(
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backends\backend_agg.py:509 in print_png
self._print_pil(filename_or_obj, "png", pil_kwargs, metadata)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backends\backend_agg.py:457 in _print_pil
FigureCanvasAgg.draw(self)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\backends\backend_agg.py:400 in draw
self.figure.draw(self.renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:95 in draw_wrapper
result = draw(artist, renderer, *args, **kwargs)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper
return draw(artist, renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\figure.py:3140 in draw
mimage._draw_list_compositing_images(
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\image.py:131 in _draw_list_compositing_images
a.draw(renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper
return draw(artist, renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\axes\_base.py:3064 in draw
mimage._draw_list_compositing_images(
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\image.py:131 in _draw_list_compositing_images
a.draw(renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper
return draw(artist, renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\axis.py:1380 in draw
tick.draw(renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper
return draw(artist, renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\axis.py:301 in draw
artist.draw(renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\artist.py:72 in draw_wrapper
return draw(artist, renderer)
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\lines.py:856 in draw
marker_trans = marker.get_transform()
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\markers.py:384 in get_transform
return self._transform.frozen()
File C:\Dev\Python\biomedical_term\Lib\site-packages\matplotlib\transforms.py:1829 in frozen
return Affine2D(self.get_matrix().copy())
KeyboardInterrupt
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